摘要
对新兴主题的识别有助于科研人员把握相关领域的研究方向。针对目前新兴主题识别以关键词词频判断为主的局限性,构建文献多属性测度模型,利用高关注度、高成长潜力度以及高关联度指标对关键词进行有效识别并筛选,最终确定新兴主题。并以精密单点定位技术为例,说明此方法的实施步骤以及可行性。研究结果表明,根据多属性测度得到的精密单点定位的新兴主题更加明确,指示性强,与该领域现实研究状况(实时精密定点定位、定位误差修正以及模糊度固定等方面)具有较高的吻合度。
The identification of emerging topics contributes to grasp the research direction of related fields for researchers. Regarding for the limitation that it is the main method to identify the emerging topics, making use of the frequency of keywords currently. In this paper, we propose to built the muti-attribute measurement model,which takes advantage of the high degree of concern, high degree of growth potential and high correlation to identify and select the keywords and determine the emerging topics finally. With the example of precise point positioning, we clarify the implementation steps and its feasibility. The result shows that according to the muti-attribute measurement model, the emerging topics of precise point positioning are more clearer as well as strongly directing. Meanwhile, comparing the reality research situation（including real-time precise point positioning, positioning errors and corrections, ambiguity fixing and so on）, it has better goodness of fit.
出处
《科学学与科学技术管理》
CSSCI
北大核心
2015年第2期34-43,共10页
Science of Science and Management of S.& T.
基金
国家社会科学基金重大项目(11&ZD140)
关键词
多属性测度
新兴主题识别
精密单点定位
mult-attribute measurement
identify emerging topics
precise point positioning
作者简介
第一作者简介：黄鲁成（1956-），男，河北徐水人，博导，教授，管理学博士，研究方向：科技与产业创新管理。
